Standardized decision support in next generation sequencing reports of somatic cancer variants.
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ABSTRACT:
SUBMITTER: Dienstmann R
PROVIDER: S-EPMC5528527 | biostudies-other | 2014 Jul
REPOSITORIES: biostudies-other
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Project description:UnlabelledNext-generation sequencing technologies expedited research to develop efficient computational tools for the identification of structural variants (SVs) and their use to study human diseases. As deeper data is obtained, the existence of higher complexity SVs in some genomes becomes more evident, but the detection and definition of most of these complex rearrangements is still in its infancy. The full characterization of SVs is a key aspect for discovering their biological implications. Here we present a pipeline (PeSV-Fisher) for the detection of deletions, gains, intra- and inter-chromosomal translocations, and inversions, at very reasonable computational costs. We further provide comprehensive information on co-localization of SVs in the genome, a crucial aspect for studying their biological consequences. The algorithm uses a combination of methods based on paired-reads and read-depth strategies. PeSV-Fisher has been designed with the aim to facilitate identification of somatic variation, and, as such, it is capable of analysing two or more samples simultaneously, producing a list of non-shared variants between samples. We tested PeSV-Fisher on available sequencing data, and compared its behaviour to that of frequently deployed tools (BreakDancer and VariationHunter). We have also tested this algorithm on our own sequencing data, obtained from a tumour and a normal blood sample of a patient with chronic lymphocytic leukaemia, on which we have also validated the results by targeted re-sequencing of different kinds of predictions. This allowed us to determine confidence parameters that influence the reliability of breakpoint predictions.AvailabilityPeSV-Fisher is available at http://gd.crg.eu/tools.
| S-EPMC3660373 | biostudies-literature
Project description:Somatic structural variants (SVs), which are variants that typically impact >50 nucleotides, play a significant role in cancer development and evolution but are notoriously more difficult to detect than small variants from short-read next-generation sequencing (NGS) data. This is due to a combination of challenges attributed to the purity of tumour samples, tumour heterogeneity, limitations of short-read information from NGS and sequence alignment ambiguities. In spite of active development of SV detection tools (callers) over the past few years, each method has inherent advantages and limitations. In this review, we highlight some of the important factors affecting somatic SV detection and compared the performance of seven commonly used SV callers. In particular, we focus on the extent of change in sensitivity and precision for detecting different SV types and size ranges from samples with differing variant allele frequencies and sequencing depths of coverage. We highlight the reasons for why some SV callers perform well in some settings but not others, allowing our evaluation findings to be extended beyond the seven SV callers examined in this paper. As the importance of large SVs become increasingly recognized in cancer genomics, this paper provides a timely review on some of the most impactful factors influencing somatic SV detection that should be considered when choosing SV callers.
| S-EPMC8138798 | biostudies-literature
Project description:PurposeTargeted next-generation sequencing (NGS) panels for solid tumors have been useful in clinical framework for accurate tumor diagnosis and identifying essential molecular aberrations. However, most cancer panels have been designed to address a wide spectrum of pan-cancer models, lacking integral prognostic markers that are highly specific to gliomas.Materials and methodsTo address such challenges, we have developed a glioma-specific NGS panel, termed "GliomaSCAN," that is capable of capturing single nucleotide variations and insertion/deletion, copy number variation, and selected promoter mutations and structural variations that cover a subset of intron regions in 232 essential glioma-associated genes. We confirmed clinical concordance rate using pairwise comparison of the identified variants from whole exome sequencing (WES), immunohistochemical analysis, and fluorescence in situ hybridization.ResultsOur panel demonstrated high sensitivity in detecting potential genomic variants that were present in the standard materials. To ensure the accuracy of our targeted sequencing panel, we compared our targeted panel to WES. The comparison results demonstrated a high correlation. Furthermore, we evaluated clinical utility of our panel in 46 glioma patients to assess the detection capacity of potential actionable mutations. Thirty-two patients harbored at least one recurrent somatic mutation in clinically actionable gene.ConclusionWe have established a glioma-specific cancer panel. GliomaSCAN highly excelled in capturing somatic variations in terms of both sensitivity and specificity and provided potential clinical implication in facilitating genome-based clinical trials. Our results could provide conceptual advance towards improving the response of genomically guided molecularly targeted therapy in glioma patients.
| S-EPMC6962483 | biostudies-literature
Project description:BackgroundGermline BRCA1/2 mutations are identified in 13-15% of ovarian cancers, while an additional 5-7% of ovarian cancers harbor somatic BRCA1/2 mutations. Beyond these mutations, germline or somatic aberrations in genes of the homologous recombination (HR) pathway such as RAD51B/C/D, PALB2, ATM, BRIP1 may confer an HR deficiency in up to 50% of ovarian tumors. Next-generation sequencing (NGS) is a high-throughput massive parallel sequencing method that enables the simultaneous detection of several mutations in entire genomes.MethodsWe performed NGS analysis in 86 patients with ovarian cancer treated in the Oncology Department of Alexandra University Hospital in order to identify the molecular landscape of germline and somatic mutations in ovarian cancer.ResultsThe genes with the highest number of pathogenic somatic mutations in high grade serous carcinoma (HGSC) patients were TP53 [68%; 34/50] and BRCA1 [22%; 11/50] followed by somatic mutations in RB1 [2%; 1/50], NF1 [2%; 1/50], BRCA2 [2%; 1/50], AKT1 [2%; 1/50], RAD50 [2%; 1/50], PIK3CA [2%; 1/50] genes. Of note, the most common TP53 genetic polymorphism was c.524G>A p.Arg175His in exon 5. Variants of unknown significance (VUS) detected in HGSC included ROS1 [26%; 13/50], RAD50 [6%; 3/50], BRCA2 [6%; 3/50], NOTCH1 [6%; 3/50], TP53 [6%; 3/50], AR [6%; 3/50]. As for germline mutations, BRCA1 [8/30; 27%] and BRCA2 [4/30; 13%] were the most common genes bearing pathogenic alterations in HGSC, while VUS germline mutations commonly affected HRR-related genes, including ATM (c.7816A>G), BRIP (c.2327 C>A), CHEK2 (c.320-5T>A).ConclusionOverall, genetic testing should be offered in most patients with ovarian cancer to identify mutations in HRR genes and determine the population that would be susceptible to poly ADP ribose polymerase (PARP) inhibitors.
| S-EPMC9754718 | biostudies-literature
Project description:BACKGROUND:Biliary tract cancers (BTCs) are uncommon and are associated with a dismal prognosis. Combinations of gemcitabine and platinum chemotherapy (gemcitabine and platinum-based therapy [GP]) form the standard approach for treating advanced BTC. To characterize the spectrum of mutations and to identify potential biomarkers for a GP response in BTC, this study evaluated the genomic landscape and assessed whether mutations affecting DNA repair were associated with GP resistance. METHODS:Pretreatment, formalin-fixed, paraffin-embedded samples from 183 BTC patients treated with GP were analyzed. Cox regression models were used to determine the association between mutations, progression-free survival (PFS), and overall survival (OS). RESULTS:When genes with an incidence?>?10% were considered, no individual gene was independently predictive of a GP response. In patients with unresectable BTC who received GP as their first-line therapy, the joint status of cyclin-dependent kinase inhibitor 2A (CDKN2A), tumor protein 53 (TP53), and AT-rich interaction domain 1A (ARID1A) was associated with PFS (P?=?.0004) and OS (P???.0001). Patients with mutations in CDKN2A and TP53 were identified as a poor-prognosis cohort with a median PFS of 2.63 months and a median OS of 5.22 months. Patients with mutant ARID1A, regardless of the single-mutation status of TP53 or CDKN2A, had similar outcomes. A patient who exhibited mutations in all 3 genes had a median PFS of 20.37 months, and OS was not reached. CONCLUSIONS:In the largest exploratory analysis of this kind for BTC, 3 prevalent, mutually exclusive mutations represent distinct patient cohorts. These mutations are prognostic and may represent a predictive biomarker for a GP response. Prospective studies to validate these findings are needed, and they should include the incorporation of therapies that exploit the genomic instability observed with these mutations in BTC. Cancer 2016;122:3657-66. © 2016 American Cancer Society.
| S-EPMC5222890 | biostudies-literature
Project description:BACKGROUND:The rapid development of next-generation sequencing (NGS) technology has continuously been refreshing the throughput of sequencing data. However, due to the lack of a smart tool that is both fast and accurate, the analysis task for NGS data, especially those with low-coverage, remains challenging. RESULTS:We proposed a decision-tree based variant calling algorithm. Experiments on a set of real data indicate that our algorithm achieves high accuracy and sensitivity for SNVs and indels and shows good adaptability on low-coverage data. In particular, our algorithm is obviously faster than 3 widely used tools in our experiments. CONCLUSIONS:We implemented our algorithm in a software named Fuwa and applied it together with 4 well-known variant callers, i.e., Platypus, GATK-UnifiedGenotyper, GATK-HaplotypeCaller and SAMtools, to three sequencing data sets of a well-studied sample NA12878, which were produced by whole-genome, whole-exome and low-coverage whole-genome sequencing technology respectively. We also conducted additional experiments on the WGS data of 4 newly released samples that have not been used to populate dbSNP.
| S-EPMC5907718 | biostudies-literature
Project description:Non-small cell lung cancer (NSCLC) is featured with complex genomic alterations. Molecular profiling of large cohort of NSCLC patients is thus a prerequisite for precision medicine. We first validated the detection performance of a next-generation sequencing (NGS) cancer hotspot panel, OncoAim, on formalin-fixed paraffin-embedded (FFPE) samples. We then utilized OncoAim to delineate the genomic aberrations in Chinese NSCLC patients. Overall detection performance was powerful for mutations with allele frequency (MAF)???5% at >500?×?coverage depth, with >99% sensitivity, high specificity (positive predictive value?>?99%), 94% accuracy and 96% repeatability. Profiling 422 NSCLC FFPE samples revealed that patient characteristics, including gender, age, lymphatic spread, histologic grade and histologic subtype were significantly associated with the mutation incidence of EGFR and TP53. Moreover, RTK signaling pathway activation was enriched in adenocarcinoma, while PI(3)K pathway activation, oxidative stress pathway activation, and TP53 pathway inhibition were more prevalent in squamous cell carcinoma. Additionally, novel co-existence (e.g., variants in BRAF and PTEN) and mutual-exclusiveness (e.g., alterations in EGFR and NFE2L2) were found. Finally, we revealed distinct mutation spectrum in TP53, as well as a previously undervalued PTEN aberration. Our findings could aid in improving diagnosis, prognosis and personalized therapeutic decisions of Chinese NSCLC patients.
| S-EPMC7005734 | biostudies-literature
Project description:Genetic testing to detect somatic alterations is usually performed on formalin-fixed paraffin-embedded tumor samples. However, tumor molecular profiling through ctDNA analysis may be particularly interesting with the emergence of targeted therapies for ovarian cancer (OC), mainly when tumor is not available and biopsy is not viable, also allowing representation of multiple neoplastic subclones. Using a custom panel of 27 genes, next-generation sequencing (NGS) was performed on tumor and matched plasma samples from 96 OC patients, which were combined in two groups (treatment naive and post-treatment). Overall, at least one somatic variant present in the tumor sample was also detected in the matched plasma sample in 35.6% of the patients, a percentage that increased to 69.6% of the treatment naive patients and 83.3% of those with stage IV disease, showing the potential of ctDNA analysis as an alternative to identify somatic variants in these patients, namely those that have predictive value for targeted therapy. In fact, of the two treatment-naive patients with somatic BRCA1 variants identified in tumor samples, in one of them we detected in ctDNA a BRCA1 somatic variant that was present in the tumor with a VAF of 53%, but not in the one that had a VAF of 5.4%. We also showed that ctDNA analysis has a complementary role to molecular unraveling of inter- and intra-tumor heterogeneity, as exemplified by one patient diagnosed with bilateral OC in which different somatic variants from both tumors were detected in ctDNA. Interestingly, as these bilateral tumors shared a rare combination of two of the three variants identified in ctDNA, we could conclude that these morphologically different tumors were clonally related and not synchronous independent neoplasias. Moreover, in the post-treatment group of patients with plasma samples collected after surgery, those with detectable somatic variants had poor prognosis when compared with patients with no detectable somatic variants, highlighting the potential of ctDNA analysis to identify patients at higher risk of recurrence. Concluding, this study demonstrated that somatic variants can be detected in plasma samples of a significant proportion of OC patients, supporting the use of NGS-based ctDNA testing for noninvasive tumor molecular profiling and to stratify patients according to prognosis.
| S-EPMC8515058 | biostudies-literature
Project description:This is a prospective, single-center, clinical study.This study is to evaluate the feasibility of genetic susceptibility screening based on the detection of tumor tissue mutations by a NGS panel.
| 2330960 | ecrin-mdr-crc
Project description:ObjectivePrecision oncology depends on translating molecular data into therapy recommendations. However, with the growing complexity of next-generation sequencing-based tests, clinical interpretation of somatic genomic mutations has evolved into a formidable task. Here, we compared the performance of three commercial clinical decision support tools, that is, NAVIFY Mutation Profiler (NAVIFY; Roche), QIAGEN Clinical Insight (QCI) Interpret (QIAGEN) and CureMatch Bionov (CureMatch).MethodsIn order to obtain the current status of the respective tumour genome, we analysed cell-free DNA from patients with metastatic breast, colorectal or non-small cell lung cancer. We evaluated somatic copy number alterations and in parallel applied a 77-gene panel (AVENIO ctDNA Expanded Panel). We then assessed the concordance of tier classification approaches between NAVIFY and QCI and compared the strategies to determine actionability among all three platforms. Finally, we quantified the alignment of treatment suggestions across all decision tools.ResultsEach platform varied in its mode of variant classification and strategy for identifying druggable targets and clinical trials, which resulted in major discrepancies. Even the frequency of concordant actionable events for tier I-A or tier I-B classifications was only 4.3%, 9.5% and 28.4% when comparing NAVIFY with QCI, NAVIFY with CureMatch and CureMatch with QCI, respectively, and the obtained treatment recommendations differed drastically.ConclusionsTreatment decisions based on molecular markers appear at present to be arbitrary and dependent on the chosen strategy. As a consequence, tumours with identical molecular profiles would be differently treated, which challenges the promising concepts of genome-informed medicine.
| S-EPMC7513637 | biostudies-literature